As the EMR “space race” peaks, clinical and health leaders are coming to understand that digitizing data does not, on its own, drive innovation or transformation.
Many are wondering what’s next. Looking ahead, the next wave in our journey towards digital transformation is Artificial Intelligence (AI).
Simply put, Artificial Intelligence is a collection of systems that sense, comprehend, act and learn.
The goal of AI in health is to drive greater “data dividends” than what we are getting from investments already made in EMRs and other systems. This dividend will be measured two ways: First, improved quality and efficiencies of systems that care for people when they are sick. Second, AI will enable a new style of “health systems” that empower consumers to better shape and manage their own health.
AI is not about creepy robots creating assembly-line healthcare. It is about systems that assist and support the wisdom and experience of well-trained clinicians in making better data-driven decisions and taking actions that best support the needs of those they serve. It does this by gathering and crunching massive amounts of data quickly and intelligently to identify patterns often overlooked or undiscovered in the traditional practice of care.
While still in the early stages, here are a few examples of AI in health.
AI to Improve Treatment Planning: Antonio Criminisi from Microsoft Research-Cambridge has developed an intelligent medical analysis system capable of improving radiation treatment planning for cancer patients. Utilizing AI, a 3D image of a tumor is created from normal CT and provides “assistive analytics” to guide treatment planners in creating the best plan to kill cancer cells while protecting healthy cells. Go here for a short video.
Medical “Clues” from Search Queries: Microsoft researchers Dr. Eric Horvitz and Dr. Ryen White recently demonstrated that by analyzing large samples of search engine queries they may be able to identify internet users suffering from pancreatic cancer, even before they have received a diagnosis of the disease.
These data scientists hope their work will lead to earlier detection of certain types of cancer. Their study was recently published in The Journal of Oncology Practice. Go here to learn more.
Speech Recognition: “Conversational” speech recognition will transform the way in which we will use and interact with data in healthcare.
The Artificial Intelligence and Research team at Microsoft recently made a major breakthrough where, when measured against the industry standard for speech recognition, a computer can recognize the words in a conversation as well as a person would. Reaching “human parity” is a historic achievement which opens the door to a new type of computing and intelligence known as “Conversation as a Platform”. From voice activated medical intelligence systems, to support for remote and home care, taking the power of human language and applying it more pervasively in healthcare computing sets the stage for true transformation. Go here to learn more.
